Future large wind power plants (WPP) will be intended to function like conventional power plants seen from the transmission system point of view, by complying with grid codes and providing ancillary services. This can be possible by integration of battery energy storage systems (BESS) into the so called Virtual Power Plants (VPP). Relatively young storage technologies, like Li-ion are constantly improving and are becoming attractive for medium-scale stationary energy storage applications because of their characteristics such as high power, high efficiency, low self-discharge, long lifetime etc.
The lifetime of battery cells is a key factor in the reliability of BESS when these are integrated into VPPs. Moreover, lifetime of BESS is a crucial factor in preliminary project stage for investigation on energy storage investment profitability. What is more, the information about the BESS State of Health (SOH), at every point, is very important since the performance of the Li-ion BESS is changing with its age.
Therefore, an accurate lifetime estimation of Li-ion batteries increases the feasibility of integrating these storage systems into VPPs. In real applications, the replacement of battery cells takes place usually before the end of their actual life, depending if the batteries are able to meet several performance requirements (in terms of capacity, efficiency etc.).
However, to develop the lifetime model for Li-ion battery is not a straightforward task since many stress factors are influencing the lifetime of the cells.
The main goal of this presentation is to present the lifetime model for a lithium iron phosphate battery (developed based on the accelerated laboratory cycle and calendar lifetime tests) and predict the lifetime of such a battery system under different mission profiles, which are specific for the following services: primary frequency regulation and wind power forecast accuracy improvement.
